{"id":"W2103797923","doi":"10.1109/icdm.2009.71","title":"Active Learning with Generalized Queries","year":2009,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Oracle; Computer science; Probabilistic logic; Ask price; Construct (python library); Artificial intelligence; Active learning (machine learning); Machine learning; Information retrieval","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000727749,0.0000811698,0.00008825507,0.00003923924,0.0001297974,0.0001072092,0.0002384357,0.00001926366,0.00004337026],"category_scores_gemma":[0.00001564073,0.00005422963,0.00002111832,0.0001814413,0.00001466953,0.0002518796,0.00003092614,0.0001607159,0.00003151493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008640021,"about_ca_system_score_gemma":0.00002243958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005238028,"about_ca_topic_score_gemma":0.000003578543,"domain_scores_codex":[0.9993951,0.00005159184,0.00006006256,0.0001964817,0.0001361566,0.0001606317],"domain_scores_gemma":[0.9997014,0.0000210525,0.0000333528,0.0001639091,0.00003103424,0.0000492316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002421533,0.00004603533,0.0009077727,0.000002100039,0.00001716138,0.0000339338,0.001690564,0.004939497,0.000717698,0.2166158,0.0005323983,0.7744728],"study_design_scores_gemma":[0.002662669,0.002797091,0.05045915,0.00004728936,0.00001403906,0.0001857455,0.00033599,0.7768273,0.01700856,0.01055466,0.1379225,0.001185002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04552025,0.00002549673,0.8945028,0.003717364,0.00005550175,0.00004927051,7.379533e-8,0.0005957176,0.05553355],"genre_scores_gemma":[0.7769491,0.000004715234,0.2109371,0.0007804195,0.00006567907,0.000002293886,0.000001204759,0.000004115327,0.01125531],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7732878,"threshold_uncertainty_score":0.221142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005007538961441209,"score_gpt":0.2262918750090593,"score_spread":0.2212843360476181,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}